The U.S. Geological Survey (USGS) maintains shoreline positions for the United States' coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release, and other associated products, represent an expansion of the USGS national-scale shoreline database to include Puerto Rico and its islands, Vieques and Culebra. The USGS, in cooperation with the Coastal Research and Planning Institute of Puerto Rico—part of the Graduate School of Planning at the University of Puerto Rico, Rio Piedras Campus—has derived and compiled a database of historical shoreline positions using a variety of methods. These historical shoreline data are then used to measure the rate of shoreline change over time. Rate calculations are computed within a geographic information system (GIS) using the DSAS version 5.1 software. Starting from a user defined baseline, measurement transects are created by DSAS that intersect the shoreline vectors. The resulting intersections provide the location and time information necessary to calculate rates of shoreline change. The overall project contains shorelines, baselines, shoreline change rates (long-term and short-term), and shoreline intersects (long-term and short-term), for Puerto Rico, and the adjacent islands of Vieques and Culebra.

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

Abstract

The PFR activities to be evaluated at end-line consists mainly of demarcation and registration of land parcels (under customary tenure) as Titre Foncier or an Attestation de Droit Coutumière. The impact evaluation aims to quantify and analyse impact of these interventions on productivity and food security disaggregated by target groups and gender.

The research questions to be answered after the endline data collection are:

1) Do PFRs (or ADCs) contribute to a perception of greater land tenure security? 2) Does improved tenure security lean to a growth in agricultural investment and/or changes to management of land? 3) Do PFRs improve access to land and rights over land among marginalised groups (women, youth and migrants)? 4) Do PFRs lead to an increased number of land transactions? 5) Does increased land security address existing constraints on land markets and lead to more efficient allocation of land resources and thereby an increase in productivity? 6) Do property rights and improved user rights result in better access to credit, possibly allowing for income diversification and thus increasing household welfare? 7) Do the new arrangements put in place during the implementation of the PFRs facilitate the resolution of land conflicts, or even prevent the emergence of these land conflicts?

Geographic coverage

The clusters were spread across the communes of Bembéréké, Sinendé and Kalalé in the north and Tchaourou in the south of the department of Borgou.

Analysis unit

• Villages
• Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The impact evaluation consists of gender and youth disaggregated data collection at base line, before the start of the intervention, in both the treatment and control villages. End line data will be collected at least 2 growing seasons after issuing of documentation to farmers.

The sample consisted of 2968 households, which were taken from 26 villages selected for the implementation of a Plan Foncier Rural (PFR), or rural landholding plans, these were the treatment villages and 27 control villages that did not benefit from a PFR.

The treatment villages were assigned by the ProPFR team in geographic clusters. The assignment of control villages followed this geographic clustering, also using further village level data with the aim of finding similar villages to maximize comparability. These clusters were spread across the communes of Bembéréké, Sinendé and Kalalé in the north and Tchaourou in the south of the department of Borgou.

Villages were selected from 11 geographical clusters of villages facing similar issues, allowing easier logistical planning for the rollout of the PFRs.

Villages selected to be part of the programme had the following characteristics: • Bordering/near to a classified national forest • At high risk of land grabbing, • The presence of another GIZ supported SEWOH project1 • Agropastoral areas (in particular the presence of transhumance –cattle driving - corridors)

But should not have the following: • Villages bordering Nigeria, within the band of increased security • MCA intervention with a PFR • Suffered serious conflict which could block the realisation of a PFR, or where a PFR may reignite past conflicts.

These characteristics alongside the desire of the implementing team to select villages in clusters, for practical reasons presented the first challenge in selecting suitable comparison villages to measure the impact of the ProPFR programme. Clustering meant that villages selected for comparison should be near the clusters to be comparable, but given the typical geography of villages in northern Benin, in that most people live in the village centre rather than spread evenly with sufficient density at the village boundary, and the lack of clearly defined village boundaries, a geographic discontinuity could not be exploited.

The second challenge in selecting comparison villages arose due to a change in the village definitions in 2013, when Benin changed from 3758 to 5290 villages which is often referred to as the “nouveau découpage”. Some old villages were split but there are no clearly defined village boundaries for the new set of villages. ProPFR selected from among the new villages, so the control villages also needed to be selected from this list. Given that the last census was collected prior to this new definition of villages, no data about the villages existed that could easily be used in matching villages to those selected for the ProPFR.

Due to this lack of data on the characteristics of the people residing in the villages, Geographical Information Systems (GIS) data were used to match each of the treatment PFR villages to a control village. Villages which were previously included in the MCA’s wave of PFRs were excluded from our study due to the difficulty in separating the effects of the two programs (MCA vs ProPFR). For each PFR village, a buffer of 20km was drawn and the union constructed for each cluster. Within this area, other villages were considered as a potential control village. Of the selection criteria, the only one applicable from GIS data is the proximity to a national forest. Where villages were close to a national forest, we attempted to match it with a control village also close to a national forest. The additional criteria on which villages were matched were the proximity to a main road (as classified by the Open Street Map shapefiles for roads) and the number of buildings in the central agglomeration of a village. Main roads are used as a proxy for access to markets and thereby potentially income levels.

The size of a village and the amount of land which can be used around it will be influenced by the size of the population as well as the presence of national forests. This strategy is similar to a Coarsened Exact Matching (CEM) strategy (see Blackwell et al, 2009), in which key characteristics are reduced (perhaps from continuous variables) to a small number of categories and matched with one another exactly. In our selection of villages, one control village was selected for each treatment village based on the key characteristics, defined as proximity to national forests (5km) and main roads (1km), and having a similar number of buildings (within 1km of the central point).

For a small number of villages, we faced an issue of common support, meaning there were no exact matches on the key characteristics. In this case other nearby villages were selected which fulfilled as many of these characteristics as possible. Data were collected on a wide range of variables following the theory of change, which states that the improvements in institutions and the PFRs may lead to improved perceived land tenure security and improved access to land for women and young men through the activities carried out by the ProPFR team. This perceived land tenure security is often seen as key to agricultural investments and thereby food security in the long term, as it allows long-term planning. The issuing of official documentation provides collateral for a loan should households wish to borrow and invest in productive activities or smooth consumption.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Survey comprised two questionnaires namely:

1. Household Questionnaire: Which comprised 14 modules with 7 rosters. Modules include household members, employment and enterprises, durable goods, housing, census of non-agricultural plots, agricultural plots, land donations, land sales, land losses, perceptions on land tenure, participation in PFR, loans, food security, young men and women.

2. Community (village) questionnaire: The community survey was administrated to each village in the form of small group interviews to collect information on the socio-economic characteristics of these villages, local land tenure structures and practices, and local prices on agricultural inputs and production. The questionnaire was organized in 9 modules: characteristics of the survey participants, land tenure, land use, land market, land conflicts, other village structures and interventions, agriculture, PFR, and village chief. The characteristics of the participants were recorded in a separate roster.

The extensive household survey was first asked to the household head with additional modules to be answered by the wife of the household head (or the female household head) as well as a young male (defined as an unmarried man, aged 18-35).

Cleaning operations

Various consistency checks were performed to ensure data quality, including systematic reports of contradictory answers and of extreme values. Throughout the data collection process, two main issues were reported. The first pertains to the sampling methodology of buildings, that led to the necessary replacement of pre-selected non-housing buildings. However, just short of 500 households required replacement. The majority of the buildings replaced were not residential buildings and were therefore not eligible for inclusion in the survey. These were replaced by the next building in the random order of buildings. The number of buildings for which nobody could be found for surveying was very low (23), thanks to the robust replacement protocol.

The second issue concerns the refusal of the village Sombouan 2 to participate in the survey. Despite several attempts, this village had to be excluded from the survey. The data were also examined for missing information for required variables, and sections. Any problems found were then reported back to the supervisors where the correction was then made.

Response rate

The response rate for

AbstractAim: We modeled isoscapes in the Northeast Pacific using satellite-based data with the main objective of testing if isoscapes defined by a few key parameters can be used as a proxy for secondary productivity. Location: Northeast (NE) Pacific; 46 – 60⁰N and 125 – 165⁰W. Time period: From 1998 to 2017 (ongoing). Major taxa studied: Zooplankton with a focus on large herbivores. Methods: Approximately 280 summer zooplankton samples were analyzed for Carbon (δ13C) and Nitrogen (δ15N) stable isotope (SI) ratios. Environmental conditions experienced by zooplankton organisms were extracted from satellite, in situ sensor and model databases. A generalized additive model approach was used to explain the spatial variability of δ13C and δ15N values and predict isoscapes. Results: Sea surface temperature (SST), sea level anomaly (SLA) and chlorophyll-a concentration emerged as the significant SI predictors. Modelled isoscapes reproduced patterns observed in δ13C and δ15N value distribution, such as a decrease from the coast to offshore. The contribution of eddies in enhancing local production in the open ocean was also well captured by the models. In the central part of the NE Pacific higher SI values were correlated with higher large copepod biomass measured by the North Pacific Continuous Plankton Recorder (CPR) survey. However, in the area off the coast of British Columbia (BC) high δ15N variability appeared to be associated with episodic intrusions of coastal waters demonstrating that caution is needed when interpreting sharp changes in SI ratios. Main conclusions: While the mechanisms driving SI ratio variability are complex, we demonstrated that a few parameters used as a proxy for some of these major mechanisms are able to successfully produce isoscape models. This approach was proven useful to provide a qualitative estimate of the secondary production, which can be particularly valuable in a region where few data are available. MethodsApproximately 280 summer zooplankton samples were analyzed for Carbon (δ13C) and Nitrogen (δ15N) stable isotope (SI) ratios. Environmental conditions experienced by zooplankton organisms were extracted from satellite, in situ sensor and model databases. A generalized additive model approach was used to explain the spatial variability of δ13C and δ15N values and predict isoscapes. Usage notesWe provide C and N isoscapes at zooplankton level for the NE Pacific for 1998-2017. The uncertainties associated with the predicted values are provided as well and should be considered when using the isoscape value. Please don't hesitate to contact the corresponding author for any questions that you might have about the isoscapes production and uses. See ReadMe file for data structure information.

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section. The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems. Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments. Method Step Description: Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed.

An overview of the different data sources with a description of the data, coverage, and time frame.

This paper describes the methodology used to define the baseline exploration suite of techniques (baseline), as well as the approach that was used to create the cost and time data set that populates the baseline. The resulting product, an online tool for measuring impact, and the aggregated cost and time data are available on the Open Energy Information website (OpenEI, http://en.openei.org) for public access. The Department of Energy's Geothermal Technology Office (GTO) provides RD&D funding for geothermal exploration technologies with the goal of lowering the risks and costs of geothermal development and exploration. The National Renewable Energy Laboratory (NREL) developed this cost and time metric included collecting cost and time data for exploration techniques, creating a baseline suite of exploration techniques to which future exploration cost and time improvements can be compared, and developing an online tool for graphically showing potential project impacts (all available at http://en.openei.org/wiki/Gateway: Geothermal).

The vast majority of SARS-CoV-2 infections are uncomplicated and do not require hospitalization, but these infections contribute to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of virologic and clinical outcomes in planning future treatment studies of COVID-19. We recently completed a randomized clinical trial of Pegylated PegIinterferon Lambda for treatment of SARS-CoV-2 infected patients conducted in the Stanford COVID-19 CTRU. Leveraging longitudinal samples and data from this trial, we define early immunebaseline and infection-induced signatures that predict the duration of viral shedding, resolution of symptoms, and immunologic memory. We recruited 108 subjects between age 18 to 75 who are PCR positive for SARS-CoV-2. The subjects were randomized to receive a single dose of Peginterferon Lambda or placebo at their first visit (day 0). In-person follow-up visits were conducted on Day 1, 3, 5, 7, 10, 14, 21, and 28, with the assessment of symptoms and vitals and collection of oropharyngeal swabs for SARS-CoV-2 testing. To profile the immune response in the COVID-19 patients, we conducted RNA-sequencing assays using blood samples collected at day 0 and day 5 after enrollment.

This data release contains foreshore slopes for primarily open-ocean sandy beaches along the East Coast of the United States (Maine through Florida). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 1997 and 2018. The shoreline positions have been previously published, but the slopes have not. An along-shore reference baseline was defined, and then 20-meter spaced cross-shore beach transects were created perpendicular to the baseline. All data points within 1 meter (along-shore) of each transect were associated with that transect. For each transect, the points on the foreshore were identified, and a linear regression was fit through the foreshore points. Beach slope was defined as the slope of the regression. The regression was evaluated at the elevation of mean high water (MHW) to yield the cross-shore location of the shoreline. In areas where more than one lidar survey is available, the slopes from each survey are provi ...

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

The National Renewable Energy Laboratory (NREL) was tasked with developing a metric in 2012 to measure the impacts of RD&D funding on the cost and time required for geothermal exploration activities. The development of this cost and time metric included collecting cost and time data for exploration techniques, creating a baseline suite of exploration techniques to which future exploration cost and time improvements can be compared, and developing an online tool for graphically showing potential project impacts (all available at http://en.openei.org/wiki/Gateway: Geothermal).

This paper describes the methodology used to define the baseline exploration suite of techniques (baseline), as well as the approach that was used to create the cost and time data set that populates the baseline. The resulting product, an online tool for measuring impact, and the aggregated cost and time data are available on the Open Energy Information website (OpenEI, http://en.openei.org) for public access.

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section. The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems. Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments. Method Step Description: 1. Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed. Surveys took place between : June 28th to July 5th 2019 July 13th to July 20th 2019 September 30th to October 9th 2019 August 10th to August 20th 2020 October 1st to October 10th 2020 April 22nd to May 5th 2021 July 27th to August 10th 2021 October 15th to October 24th 2021 June 24th to Jully 5th 2022 August 15th to August 26th 2022 2. Image analysis: A photo image analysis method with sequence (moving images) was used for the occurrence data extraction and organism counts; measurements were taken to obtain vegetation cover percentages and substrate analyzes were also carried out. Analyzes were performed with the open-source Fiji software from ImageJ. A quality/visibility rating was assigned to the analyzed image sequences. 3. Taxonomic approach: Epibenthic organisms were identified at the lowest possible taxonomic rank. A morphotype approach has been systematically used (during annotations) for the identification of sponges, hydrozoans and bryozoans, and occasionally for other organisms such as algae. Species codes were also used to distinguish certain species that could not be identified at the time of the annotations (see verbatim Identification). To eliminate observer bias, the same person analyzed all images used in this database. The organisms were identified from underwater images using a combination of identification guides and scientific papers. 4. Open nomenclature: The concept of open nomenclature has been integrated into occurrence data to support taxonomic identifications with their level of certainty, as recommended by Horton et al., 2021. The abbreviation stet. (stetit) was used when the decision not to go lower was made but an identification might be possible, whereas indet (Indeterminabilis) was used when a lower level identification was considered uncertain or impossible (see identificationqualifier). In addition, the abbreviation Confer (cf.) was used and integrated into the data tables (see occurrenceRemarks) in order to link identifications that could potentially and/or possibly be associated. 5. Remarks: Several remarks have also been incorporated (see organismRemarks, identificationRemarks and taxonRemarks), and are intended to provide additional information that may be useful to some data users; Please note that these sections could be modified or improved. 6. Quality control: The taxonomic identifications were verified through a validation process, in collaboration with various expert taxonomists. All scientific names have been checked against the World Register of Marine Species (WoRMS) to match currently recognized standards. The WoRMS match was placed in the taxonID field of the instance file. Data quality control was performed using Robistools and worms packages. All sample locations were plotted on a map for visual verification that the latitude and longitude coordinates were within the described sample area. 7. Data sharing: Only metadata and biodiversity occurrence data are shared in this dataset. The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event" file includes generic event information, including date and location. The "occurrence" file includes the original identifiers of the observed organisms, identification comments and their taxonomy. A data dictionary is also provided to explain the fields used. For access to other data or images, contact David Lévesque. For more details about the project and the methodology, a technical report (Scallon-Chouinard et al., 2022) including sampling methods with drop camera photo systems (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs) is currently available online (https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41081225.pdf); another technical report detailing photo and video image analysis methods will also be available. This project was funded by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan.

The User And Entity Behavior Analytics Market size was valued at USD 1.61 billion in 2023 and is projected to reach USD 12.10 billion by 2032, exhibiting a CAGR of 33.4 % during the forecasts period. This growth is primarily driven by the surge in cyber threats, increased focus on data security, and the adoption of cloud-based UEBA solutions. UEBA solutions provide real-time monitoring and analysis of user and entity behavior, enabling organizations to detect and respond to threats promptly. User and Entity Behavior Analytics also referred to as UEBA, is the process of controlling user and entity activity within a network to establish the occurrence of threats and unusual events. It follows the pattern of users’ activities and then detects any anomalies of users for instance unauthorized attempts at logins, attempts to transfer large amount of data or insiders threats. While it imports aspects of Machine Learning and Statistical Analysis to define baseline and parameters to detect anomalies in real-time the value of this product surpasses other conventional means of threat analysis. As a Security Information and Event Data Analysis, Solution, UEBA facilitates risk management, faster response to top-tier threats, and enhancement of an organization’s security posture by analyzing multiple tiers of information regarding users’ activity and interactions with entities within the IT landscape.

Abstract

The Cox’s Bazar Panel Survey (CBPS) was completed in August 2019, through a partnership between the Yale Macmillan Center Program on Refugees, Forced Displacement, and Humanitarian Responses (Yale Macmillan PRFDHR), the Gender & Adolescence: Global Evidence (GAGE) program, the Poverty and Equity Global Practice of the World Bank and the State and Peacebuilding Fund (SPF) administered by the World Bank. It is a representative survey of the post-2017 population of displaced Rohingya and households in host communities in the Cox’s Bazar district in Bangladesh.

The high-frequency phone tracking (HFT) surveys were built to maintain communication with baseline respondents while collecting rapid data on key welfare indicators on labor, basic needs and education. Three rounds of the HFT have been completed between 2020-2021, which have been used to produce welfare updates on the host and Rohingya population residing in Cox's Bazar, Bangladesh, particularly amidst the COVID-19 crisis.

The tracking surveys collected information across three broad welfare dimensions: labor, access to basic needs and education status of school-aged children. Round 1 collected information on labor and access to basic needs only; the module on education was added Round 2 onwards.

Geographic coverage

Cox's Bazar district and some parts of Bandarban district.

Analysis unit

Households and individuals

Universe

a) Rohingya population living in camps and b) host population within Cox's Bazar and Bandarban district.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CBPS study has a total sample size of 5,020 households (HHs), divided among three strata covering Rohingya refugees in camps and host communities in Cox’s Bazar district and some adjacent regions of Bandarban district. The CBPS HFT attempted to follow the full baseline sample of 5,020 household in each round, with no alterations or additions made to the sampling design. The baseline sampling strategy is detailed below. The three strata are defined as:
i. Rohingya refugees in camps ii. High exposure hosts: hosts within 15 km (3-hour walking distance) of camps iii. Low exposure hosts: hosts at more than 15 km (3-hour walking distance) from camps (In the datasets, the 'settlement_type' and 'stratum' variables identify the different levels at which the sample is representative)

Defining the camp strata: A two-step data collection on Rohingya refugee prevalence within host communities (i.e., outside of camps) confirmed that prevalence in host communities was low, and that this was the case not only for newer Rohingya displaced, but for the older cohort of displaced, as well. This pattern of refugee prevalence supported having one stratum for the Rohingya displaced living in camps. The sampling strategy for the CBPS therefore focused on generating representative estimates for the camp based Rohingya population in Cox’s Bazar district.

Defining the host strata: For hosts, the sampling strategy was designed to account for the differential implications of a camp-based concentration of close to a million Rohingya displaced for different areas of Cox’s Bazar. To distinguish between host communities that are differentially affected by the arrival of the Rohingya, the CBPS sampling strategy used a threshold of three hours’ walking time from a campsite to define two survey strata: (i) host communities with potentially high exposure (HE) to the displaced Rohingya, and (ii) host communities with potentially low exposure (LE).

Sampling frame: The camp sample uses the Needs and Population Monitoring Round 12 (NPM12) data from the International Organization for Migration as the sampling frame. For the host sample, a combination of the 2011 population census, Admin 4 shapefiles from the Bureau of Statistics and publicly available Google Earth imagery and OpenStreetMaps were used to develop a sampling frame.

Stages of sample selection: For camps, NPM12 divided all camps into 1,954 majhee blocks.1 200 blocks were randomly selected using a probability proportional to the size of the camp. A full listing was carried out in each selected camp block.

For hosts, a two-stage sampling strategy was followed. The first stage of selection was done at the mauza level by strata. A random sample of 66 mauzas was drawn from a frame of 286 mauzas using probability proportional to size. Based on census population size, each mauza was divided into segments of roughly 100-150 households. The second stage selected three segments from each selected mauza with equal probability of selection.

Listing and replacements: Within each selected PSU in camps (blocks) and hosts (mauza-segments), all households (100-150 on average) were listed. Of listed households, 13 households were selected at random for interview, with an additional replacement list of 5 households. More information on the sampling strategy and process can be found on the published working paper titled “Data Triangulation Strategies to Design a Representative Household Survey of Hosts and Rohingya Displaced in Cox’s Bazar, Bangladesh”.

Sampling deviation

While the original sampling strategy was designed to be representative of all camp-based Rohingya displaced, campsites with older Rohingya displaced refused to participate in the listing due to other political sensitivities. This refusal was maintained despite many attempts. Since the older Rohingya displaced were not a separate stratum, a decision was made to drop these households from the survey. Therefore, the attained sample does not contain registered refugees from the two camps – Kutupalong RC and Nayapara RC.

The host sample covers six out of eight upazilas in Cox’s Bazar District (Chakaria, Cox’s Bazar Sadar, Pekua, Ramu, Teknaf, and Ukhia upazilas) and one upazila in Bandarban District (Naikhongchhori upazila). The two upazilas not covered within the sample are the islands of Kutubdia and Maheshkhali.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The R1 tracking questionnaire was developed as a lean version of the questionnaire implemented during the CBPS baseline. The R2 and R3 questionnaires retained certain aspects of the R1 questionnaire, but also added more detailed questions on aspects such as food security (in consultation with UN-WFP) and credit-seeking and coping behavior based on findings observed in previous rounds and dynamic research needs within the COVID-19 crisis.

One questionnaire was developed per round of data collection with modules containing household level questions on access to basic needs, credit-seeking behavior, access to health services, vaccinations and individual level questions on labor market status. Any adult, knowledgeable member of the confirmed sample household were eligible to answer the household modules. The labor module was only permitted if the respondent reached was any one of the 2-3 selected adults within the household who had completed the baseline adult questionnaires.

Questionnaires were developed in English and translated into Bengali. The translations to Bengali were thoroughly reviewed by the World Bank team’s local consultants to ensure quality. Pretesting and piloting were done using the Bengali questionnaires.

All questionnaires and modules in English are provided as external resources.

Cleaning operations

Data was collected through computer-assisted telephone interviews via SurveyCTO, an ODK-based platform. Maintenance of correct questionnaire flow was ensured through in-built skips and logic checks within the programmed questionnaire.

No manual data corrections were made on submitted interviews by the data processing team. Interviews flagged as needing field corrections due to mistaken entries were re-submitted by enumerators upon strict evaluation by the project team upon close review of the concerns raised and filtered by the program automatically before closing of data collection in each round.

In addition to logic checks within the survey program itself, extensive data consistency checks and quality indicators were developed by the WB team to monitor data quality during survey implementation. Field debriefs were held frequently during the piloting phase and first week of data collection, and once a week in latter weeks to provide feedback to enumerators and gain clarity on data quality concerns.

Post data collection, structural and consistency checks have been conducted on each round dataset and in-between datasets from different rounds.

Response rate

The response rates at household level for each round of the CBPS HFT, based on the baseline sample of 5,020 and disaggregated at stratum-level are: Round 1: Overall - 67%; Camps - 54%; High exposure: 71%; Low exposure: 72% Round 2: Overall - 72%; Camps - 63%; High exposure: 81%; Low exposure: 80% Round 3: Overall - 68%; Camps - 55%; High exposure: 81%; Low exposure: 80%

*Note that the Round 1 tracking exercise was a joint-effort between the Yale Y-Rise team and the WB team. The Yale team contacted and surveyed a randomly selected 25% of baseline households, while the WB team completed the remaining 75%. The Round 1 dataset contains data on this segment of the sample only as the welfare surveys implemented by the teams were different.

The pedunculopontine tegmental nucleus of the brainstem (PPTg) has extensive interconnections and neuronal-behavioural correlates. It is implicated in movement control and sensorimotor integration. We investigated whether single neuron activity in freely moving rats is correlated with components of skilled forelimb movement and whether individual neurons respond to both motor and sensory events. We found that individual PPTg neurons showed changes in firing rate at different times during the reach. This type of temporally specific modulation is like activity seen elsewhere in voluntary movement control circuits, such as the motor cortex, and suggests that PPTg neural activity is related to different specific events occurring during the reach. In particular, many neuronal modulations were time-locked to the end of the extension phase of the reach, when fine distal movements related to food grasping occur, indicating strong engagement of PPTg in this phase of skilled individual forelimb movements. In addition, some neurons showed brief periods of apparent oscillatory firing in the theta range at specific phases of the reach-to-grasp movement. When movement-related neurons were tested with tone stimuli, many also responded to this auditory input, allowing for sensorimotor integration at the cellular level. Together, these data extend the concept of the PPTg as an integrative structure in the generation of complex movements, by showing that this function extends to the highly coordinated control of the forelimb during skilled reach to grasp movement and that sensory and motor-related information converges on a single neuron, allowing for direct integration at the cellular level. Methods All procedures were approved by the University of Otago Committee on Ethics in Care and Use of Laboratory Animals and were in accord with the “Principles of Laboratory Animal Care” (National Institutes of Health publication number 80-23, revised 1996). The behavioural and single-neuron recording methods have been previously described in detail (Hyland & Jordan, 1997; Parr-Brownlie & Hyland, 2005). Male Wistar rats (~ 400 g at the time of surgery) were trained to reach into a 25-mm-wide, 14-mm high rectangular opening 55 mm above the floor to retrieve chocolate flavoured breakfast cereal (Coco Pops™) from a tray. Once a clear paw preference for reaching had been established, chronic extracellular recording electrodes were implanted into the contralateral PPTg (anteroposterior -7.8 mm and lateral ± 2.0 mm, relative to bregma (Paxinos & Watson, 1997)) using sterile stereotaxic technique under full anaesthesia. During recording sessions, signals from electrodes were amplified and filtered (2000 -8000 x, 0.5 - 10 kHz bandpass). Extracellular action potentials from single neurons were recorded, along with marker channels for automatically or manually entered behavioural events using SciWorks software (Datawave, CO). When a suitably isolated neuron was identified, it was first recorded while animals made ~ 50 reaches. Following this, for a subset of neurons recordings were made while the rats were exposed to 50 trials of 50 ms duration 4.5 kHz tone stimuli (Med Associates Sonalert), with pseudorandom intertrial intervals.
Unit activity was analysed off-line using Spike2 software (CED, Cambridge, UK). Spikes belonging to single neurons were discriminated based on waveform shape (Fig. 1 B). For analysis of reach- and tone responses, activity was averaged over the reaching trials or tone presentations in peri-event time histograms (PETH). For reach data, PETH was centred on the interruption of an infrared beam at the position of the food. We chose this moment in the reach sequence because we were interested in determining if PPTg activity may correlate to distal skilled components of the reach-to-grasp movement, and this marks the termination of the extension phase and onset of the complex movements of the paw that are generated for grasping (Whishaw & Pellis, 1990; Hyland & Jordan, 1997; Sacrey et al., 2009). For the reach-PETH, cell activity was averaged across trials, extending for 2 seconds before and after the light-beam interrupts generated by the preferred paw (contra-lateral to the recorded hemisphere) and normalised by converting to instantaneous frequency (spikes/s) (Fig. 1 C). The first 500 ms of each PETH was used to define the baseline firing rate. PETH for slow-firing cells used 50 ms bin width and for fast-firing cells, 25 ms was used. Peaks in the PETH were defined as a group of consecutive bins that were beyond + 2 standard deviations (SD) from the mean baseline firing rate. For fast-firing cells, three consecutive 25ms bins were required, for slow-firing cells, two 50 ms bins. For inhibitions, the same criteria were applied using a threshold at – 2 SD, except for cases in low-firing cells where this threshold value was < 0 spikes/s. In these, we used the criterion defined by Galvan et al. (2016), where troughs were defined as periods in the PETH with zero bin counts that lasted ≥ 2 bins longer than any silent period in the baseline. The time of the modulation onset was defined as the leading edge of the first bin to cross the threshold, and the duration measured to the trailing edge of the last bin remained beyond the threshold. Onset times are expressed relative to the time of the light-beam interrupt which marked both the end of the ballistic extension phase of the reach and the onset of grasping. The amplitude of peaks was quantified as the mean of the in-peak bins. For analysis of firing patterns, autocorrelation histograms were calculated from selected periods around or between reaching events. For tone response PETH, similar methods were used except that the PETH was centred on the onset of the tone and a 2 ms bin width was used to capture the onset time of the short latency responses. Statistical analyses were performed using GraphPad Prism Version 8 (GraphPad Software LLC). To assist in the demarcation of the timing of overall population responses separately for 1st (+) and 1st (-) responses we performed a boxcar analysis on the average normalized Z-score in 50 ms bins using one-sample t-tests to determine deviation from baseline (Z = 0), over the period – 2 to + 1.5 s (n = 71 bins), with overall alpha = 0.05. Bonferroni correction for multiple comparisons (p = alpha/n) yielded p = 0.0007 to reject the null hypothesis. We therefore set p = 0.0001 as a conservative threshold to define a significant population-level response. To mark the onset and offset times for such responses we used the time at which p values crossed 0.001 before and after reaching the threshold. To test whether the timing of onset of the population (+) and (-) response components might differ, we performed a two-factor repeated measures ANOVA for individual neuron’s original (unsmoothed) PETH bin data for the factors RESPONSE TYPE (+, -) and TIME (71 time points from -2 to 1.5 s). To account for variation in baseline firing rate between neurons, data were normalised by calculating Z-score values for each PETH bin as the difference between the bin firing rate and the mean baseline rate (-2 to -1.5 s), divided by the standard deviation of the baseline rate. For 1st (-) neurons Z-score values were inverted so that the analysis focussed on each group’s deviation from 0, rather than the sign of the response. Sphericity was not assumed, with Geisser-Greenhouse correction as required. To objectively quantify the instantaneous frequency of regular repeated peaks in PETH and autocorrelation histograms we used the Fit Data function in Spike2 v7 to fit a sinusoid function to ranges of data that were initially visually selected as potentially containing oscillatory activity. The least-square fitting function minimised the sum of squares of the errors between the data and the fitted curve, and the Spike2 algorithm calculated an estimate of the probability that a minimum sum of squares of errors of at least this size would occur (Spike2 for Windows Manual v7, 2017).

description: During the summers of 2008 and 2009 the USGS conducted bathymetric surveys from West Ship Island, Miss., to Dauphin Island, Ala., as part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project. The survey area extended from the shoreline out to approximately 2 kilometers and included the adjacent passes. The bathymetry was primarily used to create a topo-bathymetric map and provide a base-level assessment of the seafloor following the 2005 hurricane season. Additionally, these data will be used in conjunction with other geophysical data (chirp and side scan sonar) toward constructing a comprehensive geological framework of the Mississippi Barrier Island Complex. The culmination of the geophysical surveys will provide the data necessary for scientists to define, interpret, and provide baseline bathymetry and seafloor habitat for this area and to aid scientists in predicting future geomorpholocial changes of the islands with respect to climate change, storm impact, and sea-level rise. Furthermore, these data provide information for feasibility of barrier island restoration, particularly in Camille Cut, and efforts for the preservation of historical Fort Massachusetts.; abstract: During the summers of 2008 and 2009 the USGS conducted bathymetric surveys from West Ship Island, Miss., to Dauphin Island, Ala., as part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project. The survey area extended from the shoreline out to approximately 2 kilometers and included the adjacent passes. The bathymetry was primarily used to create a topo-bathymetric map and provide a base-level assessment of the seafloor following the 2005 hurricane season. Additionally, these data will be used in conjunction with other geophysical data (chirp and side scan sonar) toward constructing a comprehensive geological framework of the Mississippi Barrier Island Complex. The culmination of the geophysical surveys will provide the data necessary for scientists to define, interpret, and provide baseline bathymetry and seafloor habitat for this area and to aid scientists in predicting future geomorpholocial changes of the islands with respect to climate change, storm impact, and sea-level rise. Furthermore, these data provide information for feasibility of barrier island restoration, particularly in Camille Cut, and efforts for the preservation of historical Fort Massachusetts.

In August of 2013, the U.S. Geological Survey (USGS) conducted geophysical surveys offshore of Petit Bois Island, Mississippi. These efforts are a continued part of the U.S. Geological Survey Gulf of Mexico Science Coordination partnership with the U.S. Army Corps of Engineers (USACE) to assist the Mississippi Coastal Improvements Program (MsCIP) and the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazards Susceptibility Project, by mapping the shallow geologic stratigraphic framework of the Mississippi Barrier Island Complex. These geophysical surveys will provide the data necessary for scientists to define, interpret, and provide baseline bathymetry and seafloor habitat for this area to aid scientists in predicting future geomorphological changes to the islands with respect to climate change, storm impacts, and sea level rise. Furthermore, these data combined with the geomorphological results will provide the properties and extent of local offshore sand sediment resources available for planning and execution of the Gulf Islands National Seashore barrier island restoration. The geophysical data were collected during one cruise (USGS Field Activity Numbers 13CCT04) aboard the University of Southern Mississippi Research Vessel Tommy Munro offshore along the gulf side of Petit Bois Island, Gulf Islands National Seashore, Mississippi. Data were acquired with the following equipment: a Systems Engineering and Assessment, Ltd., SWATHplus interferometric sonar (468 kilohertz (kHz)), an EdgeTech 424 (4-24 kHz), an EdgeTech 525i chirp sub-bottom profiling system, and a Klein 3900 sidescan sonar system. This report serves as an archive of the processed interferometric swath bathymetry and sidescan sonar data. Geographic information system data products include an interpolated digital elevation model, an acoustic backscatter mosaic, a trackline map, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

AbstractClimate change may lead to phenological mismatches, where the timing of critical events between interacting species becomes de-synchronized, with potential negative consequences. Evidence documenting negative impacts on fitness is mixed. The Cushing match-mismatch hypothesis, the most common hypothesis underlying these studies, offers testable assumptions and predictions to determine consequences of phenological mismatch when combined with a pre-climate change baseline. Here, we highlight how improved approaches could rapidly advance mechanistic understanding. We find that currently no study has collected the data required to test this hypothesis well, and 71% of studies fail to define a baseline. Experiments that clearly link timing to fitness and test extremes, integration across approaches, and null models would aid robust predictions of shifts with climate change. MethodsWe located papers relating phenological data from trophic interactions to fitness and/or performance of the consumer and/or the resource by conducting keyword searches in ISI Web of Science published up to June 2017. Keywords included phenolog* AND mismatch* OR synchron* AND interact* AND (fitness* OR performance*). If more than one measure of phenology was included, we chose the one used by the authors to calculate mismatch and examine its impact on performance. Our final review included 42 studies with 45 pair-wise species interactions (3 studies had 2 interactions). Based on the type of data collected for the consumer and resource, we classified studies as life history (i.e. one that collected data at the individual level) or one that collected data at the population or community (i.e., across species). To determine whether studies had the potential to define pre-climate change baselines, we measured the study’s time span and years of data based on the years where phenology data was available for both the consumer and resource, and consumer performance data was available. Usage notesEach observation is an individual pair-wise species interaction.

Proposed modified water deliveries to Indian Tribal Lands, Big Cypress National Preserve, and Water Conservation Area 3A require that flow and nutrient loads at critical points in the interior surface water network be measured. Defining the foundation for water levels, flows, and nutrient loads has become an important baseline for Storm Treatment Area 5 and 6 development, recent C-139 Basin flow re-diversions, and future L-28 Interceptor Canal de-compartmentaliztion including flow rerouting into the Big Cypress Preserve. Flow monitoring for the two primary flow routes for both L-28 Interceptor Canal and L-28 is key to developing this network. Data are available for L-28 Interceptor Canal below S-190, L-28 Canal above S-140, and L-28 Interceptor South .

The accurate determination of flow through the interior canal networks south of Lake Okeechobee and the C-139 basin remains critical for water budgets and regional model calibrations as defined by the Everglades Forever Act of 1994 and due to the Comprehensive Everglades Restoration Plan (CERP) initiative to reroute Big Cypress Preserve flows. The implementation of strategically located stream flow gaging points and associated data collection for nutrients has helped define future surface-water flow requirements and has provided valuable baseline flow data prior to the establishment of the recently constructed northern Storm Treatment Areas (STA’s 5 and 6) and the Rotenberger Wildlife Management Area. Generating continuous flow data at selected impact points for interior basins has complemented the existing eastern coastal canal discharge network, and has allowed for more accurately timed surface-water releases while providing flow and nutrient monitoring after recent STA implementation. A unique multi-agency experiment was conducted with much success with the focus on cooperation and development of new instrumentation and acoustic flow-weight auto-sampler protocols. The original data collection and processing was provided by three separate entities at each site with responsibilities originally allocated between the U.S. Geological Survey (USGS), the Seminole Tribe of Florida, and SFWMD. USGS provides calibration, analysis and processing of acoustic velocity meters (AVM’s) and side-looking Doppler systems and stage shaft encoders, SFWMD provides data loggers with real-time flow-weighted algorithms, and radio frequency (RF) telemetry instrumentation. The Seminole Tribe provides auto-sampler service and funds nutrient load analysis through the USGS Ocala Lab.

This dataset derives from a series of beam trawl tows conducted during several research surveys in coastal areas of the St. Lawrence Estuary, between Portneuf-sur-Mer and Pointe-des-Monts, and between June and October of 2019, 2020, 2021 and 2022. It contains catch data for fish and invertebrates (occurrence and catch weights by species), in trawl tows conducted at depths ranging from 10 to 50 meters. Data were collected in various cruises: • June 28th to July 5th 2019 (NGCC Leim) • September 30th to October 9th 2019 (NGCC Leim) • October 1st to October 10th 2020 (NGCC Leim) • April 22nd to May 5th 2021 (NGCC Perley) • October 15th to October 24th 2021 (NGCC Perley) • June 24th to July 15th 2022 (NGCC LEIM) The beam trawl used to generate this data set consists of a frame (width of 2.8 m, height of 0.8 m) equipped with a 6.5 m long net with 40 mm diamond mesh, which is lined with a net (skirt) of square mesh (5 mm) at the cod-end (length 2 m) and a protective apron (75 mm mesh) on the ventral portion. Three skid chains are linked at the base of the skates. Each station corresponds to a 5 to 10 minutes tow along an isobath at a speed of about 2 knots. At each haul, the trawl catch was placed on a sorting table on the deck and the organisms were sorted and identified at the best possible taxonomic resolution. Most taxa were independently weighed. Some invertebrates taxa were subsampled, counted and weighted in order to estimate their contribution (weight and number) to the total catch. Additionally, the first 30 fish of each species were measured and weighed individually. Taxonomic names were verified on the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match has been put in the scientificNameID field in the occurrence file. Data quality control was performed using the R packages obistools and worrms. All sampling locations were plotted on a map to perform a visual check confirming that the latitude and longitude coordinates were within the described sampling area. Data acquired during the research surveys additionally included: 1) occurrence data on epibenthic invertebrates and submerged aquatic vegetation in photo samples from a drop camera system, 2) occurrence data on fish and invertebrate taxa in video samples collected using a baited underwater video system (BUV), 3) substrate classification based on drop camera photo samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The first two items are available as independent data on the OBIS portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aimed to acquire environmental baseline data contributing to the characterization of important coastal areas and in support of evidence-based assessments and management decision-making for preserving marine ecosystems. Which contribute to the elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary between Portneuf-sur-Mer and Godbout (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as dropped photo cameras and stereoscopic baited video camera systems. The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments. This project was funded by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan.